Research-Works

Research and Publications

Md Sakibul Islam Sheikh Co-authored the work Securing Digital Services in Bangladesh: A Decentralized Identity Verification Framework Using Blockchain and Cryptography published in June 2026. [1]
I also Contributed to computer applications and technology research documented on platforms like the International Journal of Computer Applications. [1]

Datasets

I am associated with the development of Unmanned Aerial Vehicle (UAV) technology, co-authoring the UAV_SMID: UAV Sky Monitoring Image Dataset. Published in July 2026, this open-source computer vision dataset serves as a benchmark for detecting and tracking aerial objects, improving security, and optimizing sky monitoring protocols for drone-based systems. [1]

Key Details & Background

Core Project: Co-creator of UAV_SMID, a dataset focused on raw drone photography, sky exploration, and tracking algorithms. [1]
Research Focus: My work directly overlaps with modern data-driven solutions for UAV flight security, visual object classification, and airspace monitoring. [1, 2]
Digital Footprint: I also manages personal tech portfolios showcasing full-stack web development capabilities, such as: My Personal Web Developer Page.

UAV_SMID: UAV Sky Monitoring Image Dataset This dataset presents a comprehensive collection of 13,928 aerial images containing 16,229 annotated objects, specifically curated for Unmanned Aerial Vehicle (UAV) sky monitoring and airspace security. The dataset features five distinct classes: helicopter, bomb, drone, bird, and aeroplane. A key advantage of this dataset is its highly balanced class distribution, with object counts ranging from 3,162 to 3,440 per class. This balance makes it an ideal benchmark for training robust deep learning and machine learning models for aerial object detection, threat identification, and reducing false positives by distinguishing between aerial threats (drones, bombs) and natural objects (birds).

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